Embodiments relate generally to methods and apparatus for processing gate boundaries used to separate portions of datasets.
Data from a test device can be analyzed to, for example, classify one or more subpopulations of datapoints (e.g., datapoint clusters) from the data for further analysis. In some instances, geometric shapes (e.g., a polygon) can be used to define a gate boundary (can also be referred to as a gate or as a boundary) that separates the subpopulations of datapoints in a desirable fashion. The gate boundary can be manually defined and applied to the data by a user via a program such as FlowJo (TreeStar Inc., Ashland, Oreg.). In some instances, gate boundaries may not be defined in a desirable fashion (e.g., an effective fashion) based on this manual process because datapoints that fall into overlapping datapoint clusters and/or high density regions may not be readily handled (e.g., distinguished, analyzed) by a user. This can result in, for example, misclassification of datapoints and/or inaccurate statistical calculations related to the dataset. In addition, the manual definition and/or application of a gate boundary within a dataset can be relatively slow using known techniques and/or the quality of the gate boundary may not be measured in a desirable fashion. Thus, a need exists for methods and apparatus to address the shortfalls of present technology and to provide other new and innovative features.